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We examine why Cash ETRs of US domestic firms have decreased over time. Using samples from two periods – an early period (1994–1998) and a late period (2011–2015) – we regress Cash ETRs in each period on a set of explanatory variables, and allow coefficients to differ across time periods. We find that, when coefficients are allowed to differ, there is no longer a decline in the unexplained portion of Cash ETR across the two periods, and that the previously observed decline is associated with a change in the relation between firm size and Cash ETR between the two periods. Further analysis suggests that the coefficient on firm size has been declining over the past 20 years, and that controlling for this time trend alone is sufficient to explain the declining trend in Cash ETRs for domestic firms.

The purpose of this research is to examine the connections between liquidity risk, credit risk, and bank profitability in India.

In order to examine the interlinkage between liquidity risk, credit risk, and profitability of banks in India, the researcher has gathered data from all commercial banks in India from 2004–2005 to 2020–2021. The data sources included in this study encompass the International Country Risk Guide, World Development Indicators and Reserve Bank of India (RBI). Seemingly Unrelated Regression (SUR) has been utilised for the study.

Findings of this research identified that liquidity risk is inversely proportional to credit risk. Return on assets (ROA) and return on equity (ROE) are both impacted negatively by liquidity risk. ROA is impacted positively by credit risk, while ROE is impacted negatively by it. The profitability of banks is harmed by the interaction between liquidity risk and credit risk. It also shows that law and order, are beneficial to bank earnings and risk management. The capital risk-adjusted ratio has a negative relationship with bank profitability, indicating the need for better capital allocation.

The originality of this work lies in its unique contributions, It emphasises explicitly the Indian context, thereby providing insights tailored to this particular setting. It employs the SUR methodology, a statistical approach allowing for a more comprehensive data analysis. Additionally, it identifies and explores interaction effects, which can shed light on the complex relationships between variables.

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 aims to apply machine learning (ML) to identify new financial elements managers might use for earnings management (EM), assessing their impact on the Standard Jones Model and modified Jones model for EM detection and examining managerial motives for using these components.

Using eXtreme gradient boosting on 23,310 the US firm-year observations from 2012 to2021, the study pinpoints nine financial variables potentially used for earnings manipulation, not covered by traditional accruals models.

Cost of goods sold and earnings before interest, taxes, depreciation and amortization are identified as the most significant for EM, with relative importances of 40.2% and 11.5%, respectively.

The study’s scope, limited to a specific data set and timeframe, and the exclusion of some financial variables may impact the findings’ broader applicability.

The results are crucial for researchers, practitioners, regulators and investors, offering strategies for detecting and addressing EM.

Insights from the study advocate for greater financial transparency and integrity in businesses.

By incorporating ML in EM detection and spotlighting overlooked financial variables, the research brings fresh perspectives and opens new avenues for further exploration in the field.

This study aims to investigate differences between Islamic and conventional banks in Pakistan with respect to their operational efficiency, liquidity risk and asset quality. Importantly, in addition to full-fledged Islamic and conventional banks, this study also investigates a more recently emerged breed of hybrid banks, i.e. Islamic divisions of conventional banks.

Data for the period 2011–2020 was collected from financial reports of all full-fledged Islamic banks (5), Islamic banking divisions of conventional banks (8) and conventional banks (20) in Pakistan. Logistic regressions were designed to test the proposed hypotheses.

The findings suggest that full-fledged Islamic banks are operationally less efficient and experience higher liquidity risk than conventional banks. However, the asset quality of Islamic banks is better than that of conventional banks. Next, in the robustness analysis, the authors extended the sample size by adding the Islamic divisions (window) of the conventional banks; they found almost the same result except for efficiency which turned out to be non-significantly related to bank type.

The findings are beneficial for investors, depositors, consumers and bank management in understanding the financial features of such as efficiency, liquidity and liquidity risk that separate Islamic banks from conventional banks.

The findings of this study present a clear picture to bankers and practitioners about some financial features of banking systems and depict that Islamic banks are in need to improve their liquidity risk management practices to compete with conventional banks.

This study aims to investigate the effect of income and asset diversification on earnings management using discretionary loan loss provisions (LLP) in banks, and the role of risk level in mediating this effect.

A sample of banks operating in Middle East and North Africa countries was used to test the mediation model of Baron and Kenny (1986) with different measures of diversification and risk.

The results show that bank income and asset diversification have unique and combined effects on earnings management. The results also support the idea that a risk-mediating effect contributes to explaining this relationship among banks. Specifically, bank diversification strategies positively affect LLP-based earnings management by increasing bank risk. This result is relevant for conventional banks. However, only a direct and positive effect of diversification strategies on LLP-based earnings management can be observed in Islamic banks, and the indirect effect is not supported.

This study extends previous research by examining the unique and combined effects of income and asset diversification strategies on earnings management in the banking sector. Specifically, it provides new evidence that diversification strategies increase LLP-based earnings management, both directly and indirectly, through bank risk.

This paper analyzes the ex-ante determinants of asset securitization in Moroccan banks, providing a detailed exploration of factors influencing securitization in the Moroccan banking sector.

The study focuses on funding, performance, risk transfer and regulatory capital arbitrage hypotheses. By employing a probit model, we examined all Moroccan banks that securitized their assets from 2002 to 2022. Additional analyses were conducted with alternative variables and by splitting the sample into two periods, 2002–2013 and 2014–2022, to assess the impact of the regulation law 119-12 implemented in 2013 on the Moroccan securitization market.

The results indicate that the search for alternative funding sources and bank size emerge as significant factors driving securitization in Morocco. Additionally, there is limited evidence that loan portfolio quality is a decisive factor to securitize. Meanwhile, there is no evidence that securitization is driven by performance and regulatory capital arbitrage. Robustness tests further support these findings, while also suggesting that banks may engage in securitization to enhance their performance and, to a lesser extent, reduce regulatory capital.

This paper contributes to the empirical literature by identifying the determinants that drive Moroccan banks to securitize, addressing a research gap in the relatively understudied Moroccan securitization market. The findings provide valuable insights for bankers, investors and policymakers, highlighting the potential benefits of securitization and suggesting policy changes to foster a robust securitization market while ensuring financial stability.

This study aims to explore the relationship between risk governance characteristics (chief risk officer [CRO], chief financial officer [CFO] and senior directors [SENIOR]) and regulatory adjustments (RAs) in Organization for Economic Cooperation and Development public commercial banks.

Using principal component analysis (PCA) and regression models, the research analyzes a representative data set of these banks.

A significant negative correlation between risk governance characteristics and RAs is found. Sensitivity analysis on the regulatory Tier 1 capital ratio and the total capital ratio indicates mixed outcomes, suggesting a complex relationship that warrants further exploration.

The study’s limited sample size calls for further research to confirm findings and explore risk governance’s impact on banks’ capital structures.

Enhanced risk governance could reduce RAs, influencing banking policy.

The study advocates for improved banking regulatory practices, potentially increasing sector stability and public trust.

This study contributes to understanding risk governance’s role in regulatory compliance, offering insights for policymaking in banking.