Bank earnings management and analyst coverage: evidence from loan loss provisions

Hong, Yongtao; Huseynov, Fariz; Sardarli, Sabuhi; Zhang, Wei

doi:10.1007/s11156-019-00835-2

Cited by 18 publications

(27 citation statements)

References 57 publications

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“…They examine banks from 20 African countries from 2011 to 2017, and find that African banks use LLPs to reduce earnings volatility, and this behaviour is reduced in countries with greater foreign direct investment inflows. Hong et al (2019) investigate the role of loan loss provisions in analysts' decision to follow banks, and find that abnormal loan loss provisions, regardless of whether it is incomeincreasing or income-decreasing, reduce analyst coverage. Vishnani et al (2019) analyse whether earnings are managed in the banking industry in India.…”

Section: Llp and Earnings Management In Banksmentioning

confidence: 99%

Banking sector earnings management using loan loss provisions in the Fintech era

Ozili¹

2020

IJMF

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PurposeThis paper analyzes banking sector earnings management using loan loss provisions (LLPs) in the Fintech era.Design/methodology/approachRegression methodology was used to examine earnings management in the Fintech era.FindingsThe findings show evidence for bank income smoothing using LLPs. There is greater income smoothing in the second-wave Fintech era compared to the first-wave Fintech era, and the presence of strong institutions did not lower income smoothing in the second-wave era. Bank income smoothing is also greater in (1) Bank of International Settlement (BIS) and EU countries than in non-EU countries and G7 countries, (2) well-capitalized banking sectors and (3) during economic booms in the second-wave Fintech era.Practical implicationsThe competition for loans and deposits by banks and Fintech lenders in the second-wave Fintech era created additional incentives for banks to engage in income smoothing to report competitive and stable earnings.Originality/valueThe study uses a unique approach to detect country-level earnings management in the banking sector. Also, this study extends the bank earnings management literature by introducing the Fintech era as a determinant of the extent of bank earnings management.

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Section: Llp and Earnings Management In Banksmentioning

confidence: 99%

Banking sector earnings management using loan loss provisions in the Fintech era

Ozili¹

2020

IJMF

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“…The results show a highly significant and positive association between a bank's earnings propensity (EBT_LLP) and LLP, implying that better performing banks are associated with higher LLPs. We note Hong et al (2019), the results in Table 2 reveal an adjusted R-squared of 62.1%, which shows that the model utilised explains a significant variation in the LLP. We therefore utilise the results obtained in Table 2 to calculate the excess LLP which is taken to be the ALLP.…”

Section: Bank Profit Efficiency and Earnings Qualitymentioning

confidence: 71%

“…To determine the ALLP, we first estimate the discretionary LLP through a regression of the LLP among a set of independent variables identified in prior literature (e.g. Cohen et al, 2014;Dal Maso et al, 2018;Hong et al, 2019;Prior et al, 2019) in the following first-step fixed-effects regression model [5]:…”

Section: Empirical Strategy 41 Measurement Of Bank Earnings Qualitymentioning

confidence: 99%

Revisiting earnings quality and bank efficiency among East African developing economies: do systemic banking and financial crises matter?

Mathuva

Nyangu

2021

JAAR

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PurposeIn this paper, the authors investigate whether the systemic local banking crises (LBCs) and global financial crisis (GFC) impact the association between bank profit efficiency and earnings quality in developing economies.Design/methodology/approachUsing panel data spanning 29 years over the period 1991–2019 for 169 banks drawn from five East African countries, the authors perform difference-in-difference multivariate analyses using the generalised method of moments (GMM) system estimator on a sample consisting of 2,261 bank-year observations.FindingsThe results, which are robust for endogeneity and other checks, show that banks with higher profit efficiency consistently report higher quality earnings. The authors further establish that whereas systemic LBCs contribute negatively to bank earnings quality, the GFC tends to have a positive impact. These results are upheld when the joint impacts of both systemic LBCs, GFC and profit efficiency on earnings quality are considered. The positive influence of profit efficiency and GFC on earnings quality is pronounced under income-decreasing earnings management. The impacts of profit efficiency, LBCs and GFC on earnings quality appear to be non-monotonic and vary across the sampled countries.Research limitations/implicationsThe study's findings are based on banks in five developing countries within a regional economic bloc. Additional studies could focus on other economic blocs for enhanced generalisability of the findings. In addition, some of the variables examined are studied at bank-level, while other variables are at country-level. Finally, the study establishes an association between the variables of interest, and this does not necessarily imply causation.Practical implicationsThe results provide useful insights to bank regulatory and supervisory agencies on the need to exercise increased risk-based scrutiny over bank loan loss provisioning and minimum loan loss reserve requirements. From an audit perspective, auditors need to be cautious and apply an enhanced risk-based audit especially when auditing banks during and after a financial, banking or systemic crisis. Credit rating agencies need to pay closer attention to the LLPs of distressed banks. Finally, bank investors and customers should be cautious when using bank financial statements, since bank managers of poorly performing banks might engage in aggressive earnings management.Originality/valueThe study is perhaps the first to examine the joint effects of systemic LBCs on the association between bank profit efficiency and the quality of earnings in a larger dataset of banks in a developing regional economic bloc. The authors also employ the GMM system estimator in the modelling, which helps address some weaknesses in prior studies.

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“…Although analysts’ decision context is an area where research is relatively lacking, there are some follow on studies that suggest that analysts are motivated to make more accurate forecasts (Ahmed et al , 2020; Hlel et al , 2019; Mikhail et al , 1999; Rahman et al , 2019; Wang et al , 2017). Consistent with the view that analysts’ objective is to make more accurate forecasts, Hong et al (2020) and Previts and Bricker (1994) observed that analysts prefer following financial institutes with effective earnings management. Likewise, Ertimur et al (2011), Graham (1999) and Klettle (2014) suggested that reputation was also a concern when analysts are making forecasts.…”

Section: Literature Reviewmentioning

confidence: 83%

Analysts’ forecasts between last consensus and earning announcement date

Zhang

Gay

2020

JFRA

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Purpose Thomson financial database reports a monthly consensus measure of analysts’ forecasts in the third week of every month, and firms’ earnings announcement dates are usually different from the last consensus calculation date. Thus, there is a gap between the last consensus calculation date and the earnings announcement date of firms. This study aims to address the question: “Do analysts issue forecasts that are slightly higher than the consensus number to increase the accuracy of their forecasts?” Design/methodology/approach This study is based on a sample of 91,172 quarterly earnings forecasts of various firms from 1990 to 2007 made between the last consensus calculation date and quarterly earnings announcement date. Descriptive statistics and statistical tests were used to analyze the data. Findings The findings propose that contrary to expectation, analysts’ forecasts between the last consensus calculation date and earnings announcement date are smaller than the consensus number. Also, the forecasts made between the last consensus and earnings announcement date is not as informative as forecasts made at other times as they could merely reflect the analysts’ herding behavior resulting from their career concerns. Originality/value This study provides a link between the literature that studies firms’ meet or beat analysts’ earnings phenomenon and analysts’ forecast decision-making context. This study also provides useful implications for the literature on the information content of analysts’ forecasts.

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Bank earnings management and analyst coverage: evidence from loan loss provisions

Cited by 18 publications

References 57 publications

Banking sector earnings management using loan loss provisions in the Fintech era

Banking sector earnings management using loan loss provisions in the Fintech era

Revisiting earnings quality and bank efficiency among East African developing economies: do systemic banking and financial crises matter?

Analysts’ forecasts between last consensus and earning announcement date

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