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This paper aims to develop a compound measure, which is fiscal vulnerability index, provides early warning signals of fiscal sustainability problems for Türkiye's economy.

The index is constructed using twelve distinct fiscal indicators and applying the portfolio method, which considers the time-varying cross-correlation structure between the subindices.

Dynamics of the fiscal vulnerability index indicate that it accurately predicts to the well-known fiscal crisis occurring in Türkiye's recent history. As a result, such a compound measure should be used in the early identification of fiscal vulnerability in Türkiye.

The main contribution of this paper, relative to existing papers, is that a fiscal vulnerability index was constructed by employing the most contemporaneous method and evaluating its performance in terms of capturing historical stress periods.

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 paper analyzes the impact of bank opacity on financial stability in an emerging economy.

Based on a unique dataset of 31 Vietnamese commercial banks from 2007 to 2019, the paper captures earnings opacity via discretionary loan loss provisions and reflects individual bank stability through the accounting-based Z-score index and its disaggregate components. The least squares dummy variable corrected (LSDVC) approach is employed for empirical analysis.

In contradiction to most studies on developed economies, earnings management improves bank financial stability in Vietnam. Earnings management is more important for the financial stability of smaller banks. Further, the effect of financial information disclosure on bank stability is strengthened by unfavorable macroeconomic conditions, particularly economic downturns, the global financial crisis and uncertain times in banking.

This is the first study to shed light on how bank opacity influences bank financial stability in an emerging market. The evidence with the conditioning roles of bank size and macroeconomic factors, such as uncertainty in banking, is entirely novel in the related literature. Additionally, the paper contributes to a growing body of banking literature by using the LSDVC estimator to examine the association between bank opacity and bank stability.

Microfinance emerged as an essential catalyst for socio-economic development and financial inclusion to reduce poverty. Microfinance institutions cannot meet their primary objective of poverty reduction if they are not sustainable financially. With the theoretical support of profit incentive theory, this paper aims to investigate the impact of organizational structure (OS), growth outreach (average loan per borrower [ALPB] and number of active borrowers), women empowerment (percentage of women borrowers [PWB]), liquidity, leverage and cost efficiency (cost per borrower) on the financial sustainability of microfinance providers (MFPs) in India and explore the possible moderating effect of the national governance indicators (NGIs).

A financial sustainability index has been developed by using principal components analysis, including both conventional measures (return of assets and return on equity) and efficiency measures (operational self-sufficiency and financial self-sufficiency). Due to the existence of endogeneity and heteroskedasticity, this study uses two-step system generalized method of moments estimates to examine the relationships for a period of 2006 to 2018.

The finding reveals that there is a strong significant relationship between financial sustainability and its influential factors. Organizatioanl Structure, loan size, women borrowers, Gross Domestic Products and inflation enhance the financial sustainability of India’s microfinance sector. However, a number of borrowers, liquidity, leverage and operating costs negatively affect the financial sustainability of MFPs of India. The estimates demonstrate that NGIs significantly moderate the association between financial sustainability and its influential factors. The NGIs negatively affect the positive impact of Organizatioanl Structure on financial sustainability. National governance increases the positive effect of loan size (ALPB) and reduces the negative effect of a number of borrowers and leverage on the financial sustainability of MFPs of India. However, NGIs negatively affect the positive relationship between Percentage of Women Borrowers and Financial sustainability of Microfinance Providers of India.

To the best of the authors’ knowledge, this study is the first of its kind that incorporates all of the six dimensions of the National Governance Indicators (NGIs) and uses as a moderator. Secondly, a financial sustainability index has been developed for measuring the financial sustainability of Microfinance Providers (MFPs).

This study aims to examine the nexus of corporate governance with firms' financial risk-taking behavior under the corporate social responsibility (CSR) disclosures in the context of non-financial listed firms of an emerging economy.

This study investigates the relationship between corporate governance as evaluated by an index and several financial risks, including idiosyncratic, default and systematic risks. The connection of corporate governance with financial risks is also studied while considering the moderation of CSR disclosures. The data are collected from 2014 to 2018 of 73 top 100-index listed non-financial firms of Pakistan Stock Exchange (PSX). Panel regression fixed effect and 2-step generalized method of moments techniques are applied to confirm the hypothesis along with the diagnostic tests to confirm that all outcomes of models must be authentic and reliable.

The study’s findings confirm that enhancing the overall corporate governance measures resulted in an augment in the firm’s risk due to weak control and regulations prevailing in emerging economies. Moreover, CSR disclosures enhance stakeholder information, lessen information asymmetry about management policies and mitigate the risk associated with operational uncertainties.

This study has a practical implementation to policymakers that effective monitoring and controlling measures facilitate the corporate management for minimizing the financial risks. Further, the study’s findings shed light that implementing corporate governance measures is not enough to mitigate financial risks until supervisory measures in the form of CSR disclosures are not taken to analyse corporate governance effectiveness.

This paper enhances the key findings in the literature by examining the role of corporate governance measures with respect to firms’ financial risks considering the moderating role of CSR disclosures. Furthermore, this research adds to the body of knowledge regarding the implementation of monitoring measures that assist in the mitigation of firms’ financial risks hence firm value.

The purpose of this study is to empirically investigate the asymmetric effects of financial risk on Sukuk market development for a sample of Malaysian countries over the period of 2010–2021.

This study refers to the International Country Risk Guide (ICRG) in determining the financial risk factors to be studied in addition to the Malaysia financial stress index (FSI) to capture changes in financial risk level. The authors use the nonlinear autoregressive distributed lag (NARDL) model to tackle the nonlinear relationships between identified financial risk variables and Sukuk market development.

The results suggest the existence of a long-run relationship between foreign debt service stability, international liquidity stability (ILS), exchange rate stability (ERS) and financial stress level with the Sukuk market development in Malaysia. Indeed, higher ILS and ERS will boost Sukuk market size, whereas higher foreign debt services and financial stress are negatively related to Sukuk market development. Findings also indicate that the long-run positive and negative impacts of identified financial risk components on Sukuk market development are statistically different. Taking into account the role of the Sukuk market in facilitating Malaysia’s economic growth, the country should aim to keep the foreign debt-to-GDP ratio at a sustainable level.

This study points to three possible directions for future research. The first is the differential impact of financial risk components on Sukuk issuance for different Sukuk structures. As more data becomes available in the future, this area could be further explored by conducting the above analysis for different combinations of Sukuk structures and currency denominations. In addition, future researchers could also consider exploring the variability of financial risk impacts through comparative studies of the leading Sukuk-issuing countries to account for differences in regulatory frameworks and supporting infrastructure.

This study provides valuable practical and policy implications for strengthening the growth of the Sukuk market. While benefiting from the diversification benefits of funding sources to finance private or government projects and developments, Malaysia should remain vigilant to global economic conditions, foreign exchange markets and financial stress levels, as all of these factors may significantly influence investor sentiment and the rate of return offered by Sukuk issuance.

The use of the NARDL approach, which investigates the long-run effects of financial risk factors on Sukuk market development in Malaysia, makes this study a valuable addition to the literature, as there has been little research into the asymmetric effects of those variables on Sukuk market development using samples from emerging Asian markets.

The purpose of this paper is to illustrate how COVID-19 lockdowns in the USA impacted traffic safety.

The authors explored the role of vehicle, user and built environment factors on traffic fatalities in the USA, comparing results during COVID-19 lockdowns (March 19th through April 30th, 2020) to results for the same time period during the five preceding years. The authors accomplished this through proportional comparisons and negative binomial regression models.

While traffic levels were 30%–50% below normal during the COVID-19 lockdowns, all traffic fatalities decreased by 18.3%, pedestrian fatalities decreased by 19.0% and bicyclist fatalities increased by 3.6%. Fatal COVID-19 crashes were more likely single-vehicle crashes involving fixed objects or rollovers. COVID-19 traffic fatalities were most common on arterial roadways and in lower density suburban built environments. Findings suggest the importance of vulnerable road users, speed management and holistic built environment policy when pursuing safety on the streets.

The findings have road safety implications not only for future pandemics and other similar events where we would expect decreases in motor vehicle volumes (such as natural disasters and economic downturns) but also for cities that are pursuing mode shift away from personal automobiles and toward alternative modes of transportation.

Are franking credit balances priced? This paper aims to investigate the valuation of franking credit balances via a determinant analysis and value relevance analysis.

The determinant analysis examines the factors that contribute to the increasing cumulative level of franking credit balances. Value relevance studies explore whether franking credit balances are priced in the market.

The results provide strong evidence of a size effect that the level of franking credit balances increases with firm size and weak evidence of an international focus effect that the level of franking credit balances increases with international ownership. They also find an individual dividend clientele effect that the level of franking credit balances decreases with individual ownership. They find significant evidence that franking credit balances are priced in the market. One dollar of franking credit is worth 1.4 dollars in firm value. That franking balances are capitalized at more than their face value suggests that franking credits signal firms' future dividend policy. They also find that the market valuation of franking balances increases with firm size but decreases with international focus.

This study provides direct evidence that franking credit balances are capitalized into equity prices. In the determinant analysis, this paper improves Heaney's (2009) model by using the percentage of international ownership as the proxy of international focus, thus addressing the limitation of his measure. In the value relevance tests, the study uses a modified model that includes log-transformation to reduce the skewness of variables based on Tanza's (2014) value relevance model. Moreover, the study suggests that the market valuation of franking credit balances increases with firm size, which contradicts Heaney's (2009) findings.

This paper aims to highlight firms' profitability as an alternative channel by which changes in leverage could affect stock returns in an imperfect market setting. The author also analytically argues that the benefits of debt, if any, may accrue beyond the usual tax benefit channel.

The author used multivariate regression models based on firms' characteristics and the models' changes along with a two-stage least-square (2SLS) type procedure to estimate the impact of leverage changes on stock returns. The author controls for the varying arbitrage risk that is measured by forecasted idiosyncratic volatility of stock prices and overcome simultaneous or endogenous determination by using inter-temporal non-synchronous variation in leverage and control variables.

The author finds that increase in leverage increase (decrease) stock returns for firms with the gross operating profitability higher (lower) than the cost of debt. The author also finds that the variation in arbitrage risk does not substitute for the primary effect of leverage changes on stock returns.

The author's findings provide tacit support to the recent literature attempting to resolve the empirically puzzling pattern of the negative relationship between profitability and leverage. The findings suggest inclusion of profitability as a crucial asset-pricing factor in the contemporary empirical models.

The non-trivial role of profitability in determining the effect of leverage on firms' stock returns that may be useful to managers, credit analysts and policy makers to assess the impact of net profitability on any change in leverage and its ensuing consequences on firms' value.

The paper develops analytical insights into the marginal role of profitability in influencing the relationship between firms' financing decisions and firms' stock returns beyond the conventional mechanisms of tax benefits, bankruptcy costs and information asymmetry.

By introducing Stacking algorithm to solve the underfitting problem caused by insufficient data in traditional machine learning, this paper provides a new solution to the cold start problem of entrepreneurial borrowing risk control.

The authors introduce semi-supervised learning and integrated learning into the field of migration learning, and innovatively propose the Stacking model migration learning, which can independently train models on entrepreneurial borrowing credit data, and then use the migration strategy itself as the learning object, and use the Stacking algorithm to combine the prediction results of the source domain model and the target domain model.

The effectiveness of the two migration learning models is evaluated with real data from an entrepreneurial borrowing. The algorithmic performance of the Stacking-based model migration learning is further improved compared to the benchmark model without migration learning techniques, with the model area under curve value rising to 0.8. Comparing the two migration learning models reveals that the model-based migration learning approach performs better. The reason for this is that the sample-based migration learning approach only eliminates the noisy samples that are relatively less similar to the entrepreneurial borrowing data. However, the calculation of similarity and the weighing of similarity are subjective, and there is no unified judgment standard and operation method, so there is no guarantee that the retained traditional credit samples have the same sample distribution and feature structure as the entrepreneurial borrowing data.

From a practical standpoint, on the one hand, it provides a new solution to the cold start problem of entrepreneurial borrowing risk control. The small number of labeled high-quality samples cannot support the learning and deployment of big data risk control models, which is the cold start problem of the entrepreneurial borrowing risk control system. By extending the training sample set with auxiliary domain data through suitable migration learning methods, the prediction performance of the model can be improved to a certain extent and more generalized laws can be learned.

This paper introduces the thought method of migration learning to the entrepreneurial borrowing scenario, provides a new solution to the cold start problem of the entrepreneurial borrowing risk control system and verifies the feasibility and effectiveness of the migration learning method applied in the risk control field through empirical data.