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1 – 3 of 3This study aims to contribute to the debate on goodwill accounting by examining the information content of impairment losses recognized in half-yearly reports. Half-yearly reports…
Abstract
Purpose
This study aims to contribute to the debate on goodwill accounting by examining the information content of impairment losses recognized in half-yearly reports. Half-yearly reports provide a suitable context to examine the effectiveness of the impairment process. Due to IFRIC 10 requirements, indeed, managers may have incentives to avoid recognizing impairment losses at the interim reporting date.
Design/methodology/approach
The study adopts an archival approach. Based on the traditional Ohlson’s model (1995), it explores the information content of half-yearly impairment losses in the European context over the period 2007–2017.
Findings
Findings confirm the relevance of half-yearly reports and suggest that half-yearly impairment losses are significantly associated with stock prices. In particular, investors positively value companies that recognized goodwill impairment losses at the interim reporting date.
Research limitations/implications
The study contributes to the academic debate on goodwill and the effectiveness of the impairment procedure. In particular, it provides empirical evidence on the recognition of goodwill write-offs when it is possible to avoid the impairment test in the absence of indications of impairment.
Practical implications
Findings of this study can support the current debate on accounting for goodwill also in the light of the recent proposals of the IASB on the need to improve the effectiveness of the impairment test.
Originality/value
This study provides original empirical evidence on the goodwill impairment test in half-yearly reports, extending previous research that typically examines this issue in annual reports.
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Jahanzaib Alvi and Imtiaz Arif
The crux of this paper is to unveil efficient features and practical tools that can predict credit default.
Abstract
Purpose
The crux of this paper is to unveil efficient features and practical tools that can predict credit default.
Design/methodology/approach
Annual data of non-financial listed companies were taken from 2000 to 2020, along with 71 financial ratios. The dataset was bifurcated into three panels with three default assumptions. Logistic regression (LR) and k-nearest neighbor (KNN) binary classification algorithms were used to estimate credit default in this research.
Findings
The study’s findings revealed that features used in Model 3 (Case 3) were the efficient and best features comparatively. Results also showcased that KNN exposed higher accuracy than LR, which proves the supremacy of KNN on LR.
Research limitations/implications
Using only two classifiers limits this research for a comprehensive comparison of results; this research was based on only financial data, which exhibits a sizeable room for including non-financial parameters in default estimation. Both limitations may be a direction for future research in this domain.
Originality/value
This study introduces efficient features and tools for credit default prediction using financial data, demonstrating KNN’s superior accuracy over LR and suggesting future research directions.
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Mohamed Chakib Kolsi, Ahmad Al-Hiyari and Khaled Hussainey
Corporate social responsibility (CSR) has gained great attention among regulators, stock market authorities, and firms' stakeholders for many decades. In this chapter, we first…
Abstract
Corporate social responsibility (CSR) has gained great attention among regulators, stock market authorities, and firms' stakeholders for many decades. In this chapter, we first review the main regulations, standards, and laws issued by UAE federal authorities namely the Company Commercial Law of 2015, the Abu Dhabi Stock Exchange (ADX) disclosure guidance of 2019, Abu Dhabi Sustainability Week, and UAE CSR platform. Second, we present a summary of the empirical research on CSR issues in UAE context, namely in the following four fields: (1) CSR determinants both at the micro and macro levels, (2) CSR measures in the three pillars (environmental, social, and governance), (3) the impact of CSR policy and practices on financial performance/market value, (4) and the role of some mediating/moderating variables such as leadership and board gender diversity. Results show greater compliance to CSR standards among different industries and institutions but heterogenous empirical findings in the four explored fields. While there is crucial alignment with both social and environmental standards as evidenced by numerous empirical studies, additional efforts should be deployed to highlight the governance pillar through firms' discretionary reporting. Our survey provides useful directives and outcomes as it portrays both legal aspects coupled with some empirical evidence of CSR issues in the UAE context. Our study helps corporations to comply with local standards on sustainability reporting and highlights the potential economic benefits and advantages for firms adopting CSR strategy. Furthermore, it can be considered as the cornerstone for regulatory bodies in the United Arab Emirates when issuing/enhancing new standards/rules on CSR practices.
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