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This study examines the impact of debt maturity structure on stock price crash risk (SPCR) in Asian economies and the moderating effect of firm age on this relationship.

The study utilized annual data from 432 nonfinancial firms publicly listed in six Asian countries: China, Hong Kong, Japan, Singapore, Pakistan and India. The observation period covers 14 years, from 2007 to 2020. The sample was categorized into three groups: the entire sample and one group each for developing and developed Asian economies. A generalized least squares panel regression method was employed to test the research hypotheses.

The results suggest that long-term debt has a significant negative influence on SPCR in Asian economies, indicating that firms with high long-term debt experience lower future SPCR. Moreover, firm age negatively moderates this relationship, implying that older firms may experience a more pronounced reduction in SPCR due to high long-term debt. Finally, firms in developed Asian economies with high long-term debt are more effective in mitigating the risk of a significant drop in their stock prices than firms in developing Asian economies.

This study contributes to the literature in several ways. To the best of the researcher’s knowledge, this is the first of such efforts to investigate the relationship between debt maturity structure and crash risk in Asia. Additionally, it reveals that long-term debt influences SPCR directly and indirectly in Asia through the moderating role of firm age. Lastly, it is likely one of the first studies by a research team in Asia to compare the nonfinancial markets of developed and developing Asian countries.

The purpose of this article is to challenge the balanced budget practices of U.S. state governments and offer alternatives that may lead to better fiscal, economic and policy outcomes. We contend that the norm of balance may be leading U.S. states to make fiscal decisions that result in less-than-ideal outcomes, especially during economic downturns.

This is a normative article. We examine the scholarly evidence regarding balanced budget practices to assess the appropriateness of balanced budget norms. We also examine the fiscal rules followed by Eurozone countries to draw potential lessons for U.S. states.

We conclude that state governments should move away from strict norms of budget balance and seek more flexible approaches. We suggest that instead of following strict rules and norms of balance, U.S. states should consider implementing escape clauses, debt and deficit ceilings, and fiscal councils. We also suggest that the Federal Reserve be open to lending directly to states during fiscal crises to ensure that states have access to affordable credit.

The balanced budget norm has become ingrained in U.S. state budgeting practices, so much so that public officials and scholars alike rarely question it. The novel contribution of our article is to question this practice in a systematic way and propose alternative approaches.

This paper aims to explore the consumer insights and ethical concerns surrounding the online payday loan services available in the Google Play Store. This research was conducted to compare whether the presence or absence of debt collection protection acts in a country creates differences in consumer experiences regarding the ethics of payday loan collection. Specifically, the study compares customers’ experiences in both the Indonesian and US markets.

Indonesia and the USA were chosen because they have very different regulatory structures for the payday loan industry. The data was scraped using Python from 27 payday loan apps on the Indonesian Play Store, resulting in a total of 244,697 reviews extracted from the Indonesian market. For the US market, 446,010 reviews were extracted from 14 payday loan apps. The data was further analyzed using NVIVO.

The results suggest that consumers of payday loans in Indonesia and the USA hold positive views about the benefits of payday loan apps, as revealed by the word frequency and word cloud analysis. Notably, customers in both countries did not express any negative sentiments regarding the unethical interest rate charged by the payday loan, contradicting what is commonly reported in academic literature. However, a distinct pattern of unethical conduct was observed in both countries concerning marketing communication and debt collection practices. In the Indonesian market, payday loan companies were found to engage in unethical debt collection activities. In the US market, payday lenders exhibited unethical behavior in their marketing communication, particularly through deceptive advertising that makes promises to consumers that are not delivered.

The study aims to provide evidence on the various experiences of customers in the presence and absence of debt collection regulations using a novel methodology and a large sample, which strengthens the results and conclusions of the study. The study also intends to inform policymakers, particularly the Indonesian government, about the need for specific laws to regulate the debt collection process and prevent unethical practices. Ultimately, the study is expected to protect the rights of consumers from a deceptive marketing communication or unethical debt collection practices in both the Indonesian and US markets.

This paper aims to document the impact of shadow banking on non-performing loans (NPLs) of publicly listed banks in an international setting.

This paper uses the data from 27 countries and various estimation strategies to test the arguments presented in this paper. The sample covers the period between 2002 and 2020.

The empirical results suggest that banks headquartered in countries with high shadow banking activity have fewer NPLs than otherwise similar banks headquartered in countries with low shadow banking activity. The findings remain qualitatively the same in different sub-samples and after replacing the main variables with their alternate proxies. The paper also shows that this relationship is sensitive to bank-specific characteristics. Moreover, the paper also indicates that the stringency of banking regulations weakens the relationship between shadow banking and NPLs.

The study’s data limitations prevent a detailed year-by-year analysis of NPLs and shadow banking, restricting insights into their evolving dynamics. In addition, the focus on country-level shadow banking data limits the exploration of how multinational banks’ activities in various jurisdictions impact individual banks’ NPLs.

The paper not only documents the effect of shadow banking on NPLs but also shows that the relationship between shadow banking and NPLs weakens as banking regulations become more stringent.

This chapter examines the impact of sectoral indebtedness on GDP in Czechia, initially a low-indebted small open economy in which debt dynamics are becoming a major concern. The impact of household debt, non-financial corporation debt and public debt is analysed with the use of local projections based on instrumental variable estimations. The results show a more pronounced influence of household debt compared to non-financial corporation and government debt. Initially, increasing household debt stimulates short-run economic activity, but in the medium run, it limits household consumption and negatively affects output. This negative impact gradually turns into a positive effect in the long run. Non-financial corporation debt has a negative short- to medium-run impact but can have a small positive effect in the long run due to the prevalence of tradable industries. Public debt initially has a short-run negative impact, but then gradually becomes positive. Overall, the findings have implications for macroeconomic policies and the importance of monitoring financial stability.

The microfinancing sector is infamous for being prone to high credit risks due to loan defaults by its poor borrowers. Conversely, the sector is also criticized for creating debt traps for the poor. The dual nature of these peculiar problems in microfinancing causes the market failure phenomenon. Therefore, the current study explores whether public policy intervention is required to address market failure.

The study undertakes a critical review of existing literature, the news, the policy documents and other publicly available information to shape the viewpoints in this study. Constructive criticism is used to build arguments to arrive at a conceptual framework that depicts how public policy should interact with markets to address the peculiar problems of the microfinancing sector.

The findings indicate that market failure in microfinancing is real and pressing. Therefore, public policy is invited, though in its limited form. While the policy intervention may help the formal microfinancing arena by regulating the interest rates, the policy administration in the informal sector is likely to fail. Therefore, the policy should attempt to create an environment of inclusiveness. Policies that rely on coercion are not recommended. In the long run, subsidies via policy intervention are discouraged. Instead, the policy should motivate the microfinancing sector to become self-reliant.

The study is one of its kind to provide perspectives on specific market failures and policy interventions in microfinancing, particularly in economies where formal and informal sectors coexist and are equally crucial.

This chapter aims to examine the impact of whistleblowing policy (WH) on earnings management (EM) in an emerging market, Egypt. Our sample period from 2014 to 2019: the pre-whistleblowing policy period is 2014–2016 and the post-whistleblowing policy period is 2017–2019 with a total of 780 observations and the data are analyzed using ordinary least squares (OLS) regression analysis. Data are collected from annual reports, corporate governance reports, and companies’ website. The empirical analysis shows that whistleblowing policy coefficient is negative and significantly impacts EM in Egyptian firms. The result shows that when the firm adopts a whistleblowing policy, it led to decrease in EM. In addition, we provide strong and robust evidence by the difference-in-difference (DID) method to show that whistleblowing is significantly negatively associated with the extent of EM, which indicates that firms have an effective whistleblowing policy and can have several benefits. Firstly, it can help to identify and prevent illegal or unethical behavior within an organization, which can ultimately save the company from potential legal and reputational damage. Secondly, a whistleblowing policy can empower employees to speak up about any concerns they have, without fear of retaliation, which can help to create a more transparent and ethical work environment. Overall, an effective whistleblowing policy can contribute to the long-term success of a company and the broader economy. The findings of this chapter are relevant to policymakers, governments, management, employees, and shareholders to constraining EM in Egyptian firms.

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.

The primary objectives of the case study are to get the participants exposed to the issues of working capital which even profitable companies face on a day-to-day basis; give the participants an understanding of how to balance the, at times, conflicting objectives of increasing profits and sales through favorable credit terms; and expose them to the impact of increase in inventory levels and average collection period on margins in a period of slow growth. They will also learn about the concept of factoring and its uses.

The case study is about a group of companies engaged in education, steel fabrication and oil businesses owned by a single proprietor. The company was based in Fatehnagar which was part of Hyderabad district in the state of Telangana, India, and the case study traces the origins of the group from 1960s to 2021. The group was invested the surplus cash flows from the oil business to initiate and expand other businesses during this period. The economic downturn due to the COVID-19 pandemic had hit the company, particularly its oldest business – Noble Chemical Agency. The oil business was facing issues related to its growth and profitability, and the uncertainty around COVID-19-related restrictions had only augmented the fears of the management. The case study looks at issues and the dilemma which the owner of the company faced. The case study highlights various issues related to working capital management, especially related to receivables management and inventory levels faced by businesses during the slow-growth phase. It demonstrates how working capital management issues, if not resolved in time, can lead to insolvency of even a successful company with a sound business model.

The case study is meant for teaching in postgraduate management programs (Master of Business Administration and Postgraduate Diploma in Management) in the following courses: corporate finance/financial management course in the first year (the case study should be taught towards the end of the course); and management accounting courses in first year (the case study should be positioned in the middle of these courses). The case study can also be used to highlight issues related to working capital and small business management in a Management Development Programme (MDP) course for “Finance fundamentals for non-finance executives”.

Teaching notes are available for educators only.

CSS 1: Accounting and finance.

With the rapid growth of the domestic lending industry, assessing whether the borrower of each loan is at risk of default is a pressing issue for financial institutions. Although there are some models that can handle such problems well, there are still some shortcomings in some aspects. The purpose of this paper is to improve the accuracy of credit assessment models.

In this paper, three different stages are used to improve the classification performance of LSTM, so that financial institutions can more accurately identify borrowers at risk of default. The first approach is to use the K-Means-SMOTE algorithm to eliminate the imbalance within the class. In the second step, ResNet is used for feature extraction, and then two-layer LSTM is used for learning to strengthen the ability of neural networks to mine and utilize deep information. Finally, the model performance is improved by using the IDWPSO algorithm for optimization when debugging the neural network.

On two unbalanced datasets (category ratios of 700:1 and 3:1 respectively), the multi-stage improved model was compared with ten other models using accuracy, precision, specificity, recall, G-measure, F-measure and the nonparametric Wilcoxon test. It was demonstrated that the multi-stage improved model showed a more significant advantage in evaluating the imbalanced credit dataset.

In this paper, the parameters of the ResNet-LSTM hybrid neural network, which can fully mine and utilize the deep information, are tuned by an innovative intelligent optimization algorithm to strengthen the classification performance of the model.